Detecting Hardware Trojans Inserted by Untrusted Foundry Using Physical Inspection and Advanced Image Processing View Full Text


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Article Info

DATE

2018-12-13

AUTHORS

Nidish Vashistha, M. Tanjidur Rahman, Haoting Shen, Damon L. Woodard, Navid Asadizanjani, Mark Tehranipoor

ABSTRACT

Hardware Trojans are malicious changes to the design of integrated circuits (ICs) at different stages of the design and fabrication process. Different approaches have been developed to detect Trojans namely non-destructive and destructive testing. However, none of the previously developed methods can be used to detect all types of Trojans as they suffer from a number of disadvantages such as low speed of detection, low accuracy, low confidence level, and poor coverage of Trojan types. Majority of the hardware Trojans implemented in an IC will leave a footprint at the active layer. In this paper, we propose a new technique based on rapid backside SEM imaging and advanced computer vision algorithms to detect any subtle changes at the active region of transistors that can show the existence of a hardware Trojan. Here, we are only concerned with untrusted foundry problem, where it is assumed the attacker has access to a golden layout/image of the IC. This is a common threat model for those organizations that fully design their IC but need access to untrusted foundry for fabrication. SEM image from a backside thinned golden IC is compared with a low-quality SEM image of an IC under authentication (IUA). We perform image processing to both golden IC and IUA images to remove noise. We have developed a computer vision-based framework to detect hardware Trojans based on their structural similarity. The results demonstrate that our technique is quite effective at detecting Trojans and significantly faster than full chip reverse engineering. One of the major advantages of our technique is that it does not rely on the functionality of the circuit, rather the real physical structure to detect malicious changes performed by the untrusted foundry. More... »

PAGES

333-344

References to SciGraph publications

  • 2009. MERO: A Statistical Approach for Hardware Trojan Detection in CRYPTOGRAPHIC HARDWARE AND EMBEDDED SYSTEMS - CHES 2009
  • 2009. The State-of-the-Art in IC Reverse Engineering in CRYPTOGRAPHIC HARDWARE AND EMBEDDED SYSTEMS - CHES 2009
  • 2012. Introduction to Hardware Security and Trust in NONE
  • 2016. Computer Vision Metrics, Textbook Edition in NONE
  • 2017-03. Benchmarking of Hardware Trojans and Maliciously Affected Circuits in JOURNAL OF HARDWARE AND SYSTEMS SECURITY
  • 2013. Stealthy Dopant-Level Hardware Trojans in CRYPTOGRAPHIC HARDWARE AND EMBEDDED SYSTEMS - CHES 2013
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s41635-018-0055-0

    DOI

    http://dx.doi.org/10.1007/s41635-018-0055-0

    DIMENSIONS

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